Objective:To survey the status quo of the provision of palliative care services by community health service centers in Shanghai and to investigate the related influencing factors.Methods:This was a cross-sectional survey. The status quo of the provision of palliative care services in all community health service centers (249 in total) in 16 districts of Shanghai were surveyed in December 2022. The Evaluation Form for the Quality Management of Hospice Care Work in Shanghai Community Health Service Center was used for survey, which included basic information, talent team, related department, medical services, research and training, and health education, etc. The data were collected up to November 30, 2022. The 16 districts were divided into three areas: central city (80 centers), suburb (92 centers) and exurb (77 centers). The scores of different districts were compared and the influencing factors were analyzed.Results:The average self-evaluation score of community hospice care service in 16 districts was 69.42 points. Changning District in the central city had the highest self-evaluation score (87.32 points) and Fengxian District in the exurb had the lowest self-evaluation score (44.59 points). The total scores of hospice service in central urban area and suburban area [(73.99±16.96) and (75.61±10.69) points] were higher than those in the exurbs [(56.81±20.82) points], and the scores in central urban area and suburban area were also higher than those in the exurbs ( P<0.05). Multivariate regression analysis showed that the community location, the registration status of hospice department, inpatient ward facilities, and availability of hospice information platform were independent influencing factors of community self-rating scores ( P<0.05). Conclusion:Hospice care services have been fully covered in Shanghai community health service centers, and the current situation of community hospice care services in the central city and the suburbs is better than that in the exurbs.

Objective: To explore the causal link of cumulative ecological risk and future orientation with health risk behaviors among higher vocational college students, so as to provide reference for reducing and preventing health risk behaviors among higher vocational college students. Methods: A longitudinal follow up study was conducted on 612 students using convenience sampling from 2 vocational colleges in Hunan Province. The Cumulative Ecological Risk Scale, Future Orientation Scale, and Health Risk Behavior Scale were used during three follow up visits (T1: September 2022, T2: June 2023, T3: March 2024), and a cross lagged panel model was constructed to examine the longitudinal causal relationship of cumulative ecological risk, future orientation and health risk behaviors. Analysis of longitudinal intermediary effect between variables by Bootstrap. Results: The cumulative ecological risk scores of T1, T2 and T3 among higher vocational college students were (2.94±1.44,2.99±1.63,3.02±1.54), future orientation scores (40.49±4.71,41.51±5.72,41.06±4.35) and health risk behavior scores (3.73±2.01,3.49±2.00,3.23±2.00). The results of repeated measures ANOVA showed that the future orientation score of T2 was higher than that of T1, and the main effect of measurement time was statistically significant ( F=5.09，P＜0.01,η 2=0.02). The health risk behavior score of T1 was higher than that of T2, and the health risk behavior score of T2 was higher than that of T3, and the main effect of measurement time was statistically significant ( F=10.12，P＜0.01,η 2=0.03).The cross lagged model showed good adaptability, with χ 2/df =7.20 ( P <0.01), relative fitting indicators GFI=0.98, CFI=0.99, TLI=0.96, IFI=0.99, NFI =0.99, and absolute fitting indicator RMSEA =0.06. Among them, the T1, T2 cumulative ecological risk showed negatively predictive effects on T2, T3 future orientation ( β =-0.24, -0.47 ), and T1, T2 cumulative ecological risk positively predicted T2, T3 health risk behavior ( β =0.20, 0.24), while T1, T2 future orientation negatively predicted T2, T3 health risk behavior ( β =-0.25, -0.18) ( P ＜0.01). Bootstrap test analysis found that T2 future orientation had a longitudinal mediating effect ( β=0.04, P ＜0.01) on the T1 cumulative ecological risk and T3 health risk behavior. Conclusions The accumulation of ecological risk among higher vocational college students can positively predict health risk behaviors, while future orientation can negatively predict healthrisk behaviors. Moreover, future orientation plays a longitudinal mediating role between accumulated ecological risks and health risk behaviors.

Objective: To explore the association of latent profiles of mobile phone dependence and self control with physical exercise among junior high school students, so as to provide references for the prevention of mobile phone dependence and the improvement of self control among junior high school students. Methods: From April to May 2024, a stratified random cluster sampling method was used to select a total of 2 311 students from grade 7 to grade 9 in three public junior high schools in Xiangxi Autonomous Prefecture, Hunan Province. Latent profile analysis was conducted to identify the latent profiles of mobile phone dependence and self control among junior high school students. Pearson correlation analysis was used to examine the correlation between mobile phone dependence and self control, and Chi square test was used to analyze the distribution differences of latent profiles of adolescents across different demographic characteristics. Multiple Logistic regression analysis was applied to explore the association between mobile phone dependence, self control, and physical exercise. Results: Four latent profiles of mobile phone dependence and self control were identified: low dependence-moderate self control group ( n =885, 38.3%), moderate dependence-low self control group ( n =910, 39.4%), high dependence-no self control group ( n =232, 10.0%), and no dependence-high self control group ( n =284, 12.3%). Significant differences were observed in the distribution of latent profiles across gender, grade and only child status ( χ 2=10.85, 35.72, 13.85， P <0.05). Logistic regression analysis showed that, after controlling for demographic variables, compared with the low dependence-moderate self control group, physical exercise was negatively associated with the moderate dependence-low self control group ( OR =0.79) and the high dependence-no self control group ( OR =0.81), while positively associated with the no dependence-high self control group ( OR =1.58) ( P <0.01). Conclusions The influence of physical exercise on junior high school students different potential profile types of mobile phone dependence and self control is different. Schools and families should adopt targeted physical exercise interventions based on the characteristics of different profiles to promote the physical and mental health of junior high school students.

Objective: To analyze the heterogeneity of mobile phone dependence development trajectory in middle school students and its association with loneliness and selfcontrol ability, so as to provide reference for the prevention of mobile phone dependence in middle school students. Methods: A total of 941 grade 1 students from 4 public middle schools in Xiangxi Autonomous Prefecture, Hunan Province were selected for the followup survey by random cluster sampling from October 2023 to April 2024 and October 2024. Mobile Phone Addiction Index (MPAI), University of California, Los Angeles Loneliness Scale-20 (UCLA-20) and Selfcontrol Scales (SCS) were used for questionnaire survey. The heterogeneity of the developmental trajectory of middle school students mobile phone dependence was analyzed by the latent growth curve model (LGMM), and the influencing factors of the developmental trajectory of middle school students mobile phone dependence were explored by multiple Logistic regression analysis. Results: The development trajectory of middle school students mobile phone dependence could be divided into four categories: C1 "low risk slow decline group (n=438,44.6%)", C2 "medium risk slow rise group (n=272,29.7%)", C3 "high risk rapid decline group (n=73,8.6%)" and C4 "high risk rapid rise group (n=158,17.1%)". There were significant differences in the distribution of mobile phone dependence development track heterogeneity subgroups among sex, only child, lodging, and leftbehind students (χ2=117.79, 44.88, 37.09, 130.50, P <0.01). The results of the multinomial Logistic regression model analysis showed that, with C1 group as the reference, C2, C3, and C4 were positively correlated with students loneliness [OR(95%CI)=1.04 (1.02-1.06), 1.11(1.08-1.14), 1.12(1.09-1.14)]; C2 and C4 groups were negatively correlated with students selfcontrol [OR(95%CI)=0.97(0.96-0.99), 0.95(0.93-0.97)] (P<0.01). Conclusions The development trajectory of mobile phone dependence among middle school students is heterogeneous. Reducing the loneliness of individuals and cultivating good selfcontrol ability are helpful to alleviate mobile phone dependence behavior among middle school students.

Objective: To explore the latent class characteristics and related factors of health risk behaviors among higher vocational college students (referred to as vocational students) in the Wuling Mountain Area, so as to provide references for promoting their healthy development and formulating effective intervention measures. Methods: From April to June 2024, a stratified random cluster sampling method was used to survey 1 737 students from three higher vocational colleges in the Wuling Mountain Area (Xiangxi in Hunan, Enshi in Hubei, and Tongren in Guizhou). The study employed the Health risk Behavior Questionnaire for College Students, the Parent-Child Relationship Scale, the Social Support Scale, and the School Connection Scale for data collection. Latent class analysis (LCA) was used to examine the heterogeneous distribution characteristics of health risk behaviors among vocational students, and multivariate Logistic regression was applied to analyze the related factors of latent classes. Results: The LCA results identified three latent classes based on 12 health risk behaviors: the comprehensive high risk group (151 students, 8.7% ), the psychological distress group (883 students, 50.8%), and the low risk group (703 students, 40.5%). The distribution of latent classes showed statistically significant differences in gender and only child status ( χ 2=121.25, 9.85, both P <0.05). The low risk group scored higher in parent-child relationship (29.26±6.19), social support (63.98±18.16), and school connection (35.97± 7.71 ) compared to the comprehensive high risk group (27.28±6.03, 57.67±15.60, 32.97±7.55) and the psychological distress group (27.52±5.19, 62.06±14.54, 33.80±6.14) ( F =20.37, 23.51, 9.89, all P <0.05). Multivariate Logistic regression revealed that boys( OR =3.29) were more likely to belong to the comprehensive high risk group, social support ( OR =0.03, 0.21) and school connection ( OR =0.92, 0.96) were less likely to belong to both the comprehensive high risk and psychological distress groups (all P < 0.05). Conclusions There are three potential categories of healthharmful behaviors among vocational college students in Wuling Mountain Area. Schools, families and society should enhance the levels of parent-child relationship, school connections and social support for vocational college students of different categories to promote their physical and mental health development.

Objective: To explore the dynamic relationship between depressive symptom and non-suicidal self-injury(NSSI) behavior among rural left behind junior high school students, as well as the mediating role of social support, so as to provide a reference for preventing the occurrence of behaviors that endanger the physical and mental health of rural adolescents. Methods: In October 2023, 828 rural left behind junior high school students from four counties and cities in Xiangxi Autonomous Prefecture, namely Luxi County, Huayuan County, Baojing County and Longshan County, were selected by cluster random sampling for a one year follow up investigation (T1:October 2023,T2:April 2024,T3:October 2024). Depressive symptom, NSSI behavior and social support of junior high school students were evaluated by using the Patient Health Questionnaire-9(PHQ-9),Adolescent Non suicidal Self injury Assessment Questionnaire (ANSAQ), and Social Support Scale for University Students(SSSUS). A cross lag panel model was constructed to analyze the dynamic relationship between depression symptom and NSSI behavior, as well as the longitudinal mediating role of social support. Results: The levels of depressive symptoms(T1-T3:150.00±5.88，14.29±7.52，13.97±6.70) and NSSI behavior (T1-T3:6.91±4.65，6.10±3.92，4.79±3.51) of rural left behind junior high school students both showed downward trends ( F =13.41, η 2=0.02; F =50.49, η 2=0.06), the level of social support (59.17±14.68，62.27±15.36，61.82±15.90) showed an upward trend ( F =20.94, η 2=0.03), and the depressive symptom and NSSI behavior of girls were higher than those of boys ( F =19.91, η 2=0.02; F =4.57, η 2=0.01)(all P <0.05). The positive predictive relationships between depressive symptom and NSSI behavior among rural left behind junior high school students [depressive symptom of T1 positively predicted NSSI behavior of T2 and T3 ( β =0.10, 0.16); depressive symptom of T2 positively predicted NSSI behavior of T3 ( β =0.14), all P <0.01]. Social support during the T2 period played a partial mediating role between depressive symptom in T1 and NSSI in T3, with a mediating effect of 0.02 (95% CI =0.01-0.17, P <0.05). Conclusions Depressive symptom positively predict the occurrence of NSSI behavior among rural left behind junior high school students. Social support is an important mediating factor in alleviating the influence of depressive symptoms on the occurrence of NSSI behavior. It should prevent and reduce the occurrence of depression symptoms and NSSI behavior by improving the social support level of rural left behind junior high school students.

Objective To study its effect and mechanism of epigallocatechin-3-gallate(EGCG)on the generation of Aβ42 in N2a/APP695swe cells.Methods The N2a/APP695swe cells were cultured in vitro and treated with different concentrations of EGCG(or in combination with LXRβ antagonist GSK2033).The DM-SO group and wild type N2a/wt group were set.The cellular survival rate was detected by the MTT assay;ELISA was used to detect the Aβ42 level;Western blot was used to detect the expression levels of LXRβ,RXRα,ABCA1,caveolin-1 and BACE1 proteins.Results The cellular survival rate and Aβ42 level in the 20,40 μmol/L EGCG cells groups were significantly improved compared with the other groups(P＜0.05),more-over which showed the concentration dependence(P＜0.05).After 20 μmol/L EGCG action,the expression levels of LXRβ,RXRα and ABCA1 protein were increased,the expression levels of caveolin-1 and BACE1 pro-tein were significantly decreased,and the differences were statistically significant(P＜0.05);after treating the cells by combining with GSK2033,the expression levels of LXRβ,RXRα and ABCA1 protein were significantly decreased and caveolin-1 and BACE1 protein expression levels were significantly increased(P＜0.05).Conclu-sion The generation of Aβ42 in N2a/APP695swe cells could be inhibited by EGCG,thus which inhibits the cellular proliferation,and its mechanism may be related to EGCG activating the LXRβ-RXRα-ABCA1 path-way,and then inhibiting the expression of caveolin-1 and BACE1.

Objective: To explore the influence of social support and school connectedness on the developmental trajectory of self efficacy in adolescents and analyze its subgroup effects, so as to provide a basis for enhancing adolescents self-efficacy. Methods: Using a cluster random sampling method, 930 first year middle school students from four schools in Xiangxi Autonomous Prefecture, Hunan Province, were selected for three longitudinal surveys in October 2023 (T1), April 2024 (T2), and October 2024 (T3). The General Self-efficacy Scale (GSES), Social Support Scale (SSS), and School Connectedness Scale (SCS) were administered. Latent growth mixture modeling (LGMM) was used to identify different developmental trajectories of self-efficacy in early adolescence. Multivariate Logistic regression was employed to examine the associations of self-efficacy trajectories with social support and school connectedness in adolescents. Results: The developmental trajectory of self-efficacy in adolescents was classified into three categories:category 1 was low efficacy-rapid growth group (53 students, 6.6%), category 2 was moderate efficacy-stable growth group (793 students, 84.1%), and category 3 was high efficacy-rapid decline group (84 students, 9.3%). Using the low efficacy- rapid growth group as the reference, students with higher social support were more likely to belong to the moderate efficacy- stable growth group ( OR=1.06, 95%CI =1.03-1.08) and the high efficacy-rapid decline group ( OR=1.06, 95%CI = 1.03 -1.09), students with higher school connectedness were more likely to belong to the high efficacy-rapid decline group ( OR= 1.10 , 95%CI =1.03-1.18) (all P <0.05). Subgroup analysis revealed significant effects for boarding status (low efficacy-rapid growth group at T1, t =2.10; high efficacy-rapid decline group in social support, t =-2.15) and only child status (moderate efficacy-stable growth group at T2, t =2.05) (all P <0.05). Conclusions The developmental trajectory of self-efficacy in adolescents exhibits group heterogeneity, with boarding status and only child status showing subgroup effects. Enhancing social support and school connectedness can help improve self-efficacy in adolescents.

Objective:To analyze the developmental trajectories of depressive symptoms in middle school students and their relationship with school connection and self-efficacy,and to provide evidence for the prevention of early adolescent depressive symptoms.Methods:In March(T1),June(T2),December(T3),809 middle school students were followed up in 2023 using the Patient Health Questionnaire-9(PHQ-9),School Connection Scale(SCS)and General Self-Efficacy Scale(GSES).The heterogeneity of the developmental trajectory of depressive symptoms in early adolescents was analyzed by the latent variable growth mixed model(LGMM),and the relation-ship between the developmental trajectory of depressive symptoms and school connection and self-efficacy was ana-lyzed by multiple logistic regression.Results:LGMM results showed that the development trajectory of early de-pressive symptoms in adolescents could be divided into:"low level-remission group"(65.3％),"low level-stable group"(28.6％)and"medium level-worsening group"(6.1％).Logistic regression analysis showed that male students(OR=0.62,95％CI=0.44-0.86)and school connection(OR=0.91,95％CI=0.88-0.94)were the protective factors in the"low level-stable group".Boys(OR=0.26,95％CI=0.13-0.53),school connection(OR=0.93,95％CI=0.88-0.98),and self-efficacy(OR=0.90,95％CI=0.85-0.96)were the protective fac-tors in the"medium level-worsening".Conclusion:There is heterogeneity in the developmental trajectory of early adolescent depressive symptoms,and school connection and self-efficacy are protective factors for the development of early adolescent depressive symptoms.

Objective:To analyze the developmental trajectories of depressive symptoms in middle school students and their relationship with school connection and self-efficacy,and to provide evidence for the prevention of early adolescent depressive symptoms.Methods:In March(T1),June(T2),December(T3),809 middle school students were followed up in 2023 using the Patient Health Questionnaire-9(PHQ-9),School Connection Scale(SCS)and General Self-Efficacy Scale(GSES).The heterogeneity of the developmental trajectory of depressive symptoms in early adolescents was analyzed by the latent variable growth mixed model(LGMM),and the relation-ship between the developmental trajectory of depressive symptoms and school connection and self-efficacy was ana-lyzed by multiple logistic regression.Results:LGMM results showed that the development trajectory of early de-pressive symptoms in adolescents could be divided into:"low level-remission group"(65.3％),"low level-stable group"(28.6％)and"medium level-worsening group"(6.1％).Logistic regression analysis showed that male students(OR=0.62,95％CI=0.44-0.86)and school connection(OR=0.91,95％CI=0.88-0.94)were the protective factors in the"low level-stable group".Boys(OR=0.26,95％CI=0.13-0.53),school connection(OR=0.93,95％CI=0.88-0.98),and self-efficacy(OR=0.90,95％CI=0.85-0.96)were the protective fac-tors in the"medium level-worsening".Conclusion:There is heterogeneity in the developmental trajectory of early adolescent depressive symptoms,and school connection and self-efficacy are protective factors for the development of early adolescent depressive symptoms.